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CODE 98458
ACADEMIC YEAR 2023/2024
CREDITS
SCIENTIFIC DISCIPLINARY SECTOR ING-INF/04
LANGUAGE English
TEACHING LOCATION
  • GENOVA
SEMESTER 1° Semester
TEACHING MATERIALS AULAWEB

OVERVIEW

Smart systems incorporate functions of sensing, actuation, and control in order to describe and analyze a situation, and make decisions based on the available data in a predictive or adaptive manner, thereby performing smart actions. In most cases the “smartness” of the system can be attributed to autonomous operation based on closed loop controlenergy efficiency, and networking capabilities.

Smart systems typically consist of diverse components:

  • Sensors for signal acquisition
  • Elements transmitting the information to the command-and-control unit
  • Command-and-control units that take decisions and give instructions based on the available information
  • Components transmitting decisions and instructions
  • Actuators that perform or trigger the required action

(https://en.wikipedia.org/wiki/Smart_system) 

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims at providing modeling and methodological approaches to sensing, actuation, and control in order to describe and analyze a system, and make decisions based on the available data in a distributed, predictive and/or adaptive manner, thereby performing “smart actions”. The student will approach such smart systems by studying proper models and methods in different applicative contexts, such as smart power grids, connected autonomous vehicles and platooning, energy efficient buildings, distributed logistics, and environmental monitoring.

AIMS AND LEARNING OUTCOMES

AIMS: make the student aware of control and systems modelling techniques which can now be applied through the availability of networks of smart sensors, such as the ones based on Internet of Things.

LEARNING OUTCOMES: technical and methdological skills in the design of a smart system with the possibility to control it according to Model PRective Control, Robust Control, and Distributed Control approaches. 

PREREQUISITES

basic control and systems modelling techniques in Matlab and Simulink

TEACHING METHODS

Project and oral interview

SYLLABUS/CONTENT

Introduction to complex systems

  • Networked and smart systems
  • Complex Systems Design Overview
  • Strategic, tactical, and operational decision making

Control of a complex system

  • Modelling predictive control (MPC)
    • Feedback systems
    • Receding horizon
    • Linear predictive control
    • MPC vs Linear Quadratic Control
  • Dual decomposition
  • Minimax team decision problems
  • Generalised linear quadratic control
  • Applications: energy efficient buildings, smart greenhouses, vehicle platooning, smart power grids.

Strategic and tactical decisions

  • Risk based routing in a network: averse beahaviour and fuzzy objectives
  • Vehicle routing versus inventory routing problems
  • Applications: transport of dangerous goods

Reliability, Availbility, Maintenance, and Safety of a complex system

RECOMMENDED READING/BIBLIOGRAPHY

Different authors

Videos and papers at https://systemsacademy.io/

 

A. Bemporad, W.P.M.H. Heemels, and M. Johansson (Eds.),

Networked Control Systems, vol. 406 of Lecture Notes in Control and Information Sciences

Springer-Verlag, Berlin Heidelberg, 2010

ISBN 978-0-85729-033-5

C. Bersani, R. Sacile

Trasporto di merci pericolose su strada: Valutazione del rischio e caso di studio

Edizioni Accademiche Italiane, 2018

ISBN 978-620-2-08697-4

T. Nowakowski, et al.

Safety and Reliability: Methodology and Applications

CRC Press, 2014.

ISBN 9781138026810

A. Rantzer

Dynamic Dual Decomposition for Distributed Control

2009 American Control Conference

H. Dagdougui and R. Sacile

Decentralized Control of the Power Flows in a

Network of Smart Microgrids Modeled

as a Team of Cooperative Agents

Ieee Transactions on Control Systems Technology, 2014

A. Gattami et al.

Robust Team Decision Theory

Ieee Transactions on Automatic Control, 2012

A. Gattami

Generalized Linear Quadratic Control

Ieee Transactions on Automatic Control, 2010

C. Bersani et al.

Distributed Product Flow Control in a Network of Inventories With Stochastic Production and Demand

IEEE Access, 2019

L. Zero et al.

Two new approaches for the bi-objective shortest path with a fuzzy objective applied to HAZMAT transportation

Journal of hazardous materials, 2019

C. Bersani et al.

Distributed robust control of the power flows in a team of cooperating microgrids

IEEE Transactions on Control Systems Technology, 2016

 

Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities

TEACHERS AND EXAM BOARD

Exam Board

ROBERTO SACILE (President)

ENRICO ZERO

MICHELE AICARDI (President Substitute)

LESSONS

Class schedule

L'orario di tutti gli insegnamenti è consultabile all'indirizzo EasyAcademy.

EXAMS

EXAM DESCRIPTION

The exam is based on the design and implementation of a smart system, generally in Matlab/Simulink environment. This project will be discussed in an interview, where other contents of the course will also be asked.

ASSESSMENT METHODS

During the interview, the student must show to have the ability to modify the project according to different specifications given. In addition, he/she must show to have a clear view of the other methdological and technological content of the course

Exam schedule

Data Ora Luogo Degree type Note
26/12/2023 15:00 GENOVA Orale
17/01/2024 11:00 GENOVA Orale
02/02/2024 11:00 GENOVA Orale
06/06/2024 11:00 GENOVA Orale
20/06/2024 11:00 GENOVA Orale
15/07/2024 11:00 GENOVA Orale
02/09/2024 11:00 GENOVA Orale